Publications by authors named "Amanda Lans"

6 Publications

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Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review.

Acta Orthop 2021 Apr 18:1-9. Epub 2021 Apr 18.

Orthopedic Oncology Service, Massachusetts General Hospital, Harvard Medical School, Boston, USA;

Background and purpose - External validation of machine learning (ML) prediction models is an essential step before clinical application. We assessed the proportion, performance, and transparent reporting of externally validated ML prediction models in orthopedic surgery, using the Transparent Reporting for Individual Prognosis or Diagnosis (TRIPOD) guidelines.Material and methods - We performed a systematic search using synonyms for every orthopedic specialty, ML, and external validation. The proportion was determined by using 59 ML prediction models with only internal validation in orthopedic surgical outcome published up until June 18, 2020, previously identified by our group. Model performance was evaluated using discrimination, calibration, and decision-curve analysis. The TRIPOD guidelines assessed transparent reporting.Results - We included 18 studies externally validating 10 different ML prediction models of the 59 available ML models after screening 4,682 studies. All external validations identified in this review retained good discrimination. Other key performance measures were provided in only 3 studies, rendering overall performance evaluation difficult. The overall median TRIPOD completeness was 61% (IQR 43-89), with 6 items being reported in less than 4/18 of the studies.Interpretation - Most current predictive ML models are not externally validated. The 18 available external validation studies were characterized by incomplete reporting of performance measures, limiting a transparent examination of model performance. Further prospective studies are needed to validate or refute the myriad of predictive ML models in orthopedics while adhering to existing guidelines. This ensures clinicians can take full advantage of validated and clinically implementable ML decision tools.
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http://dx.doi.org/10.1080/17453674.2021.1910448DOI Listing
April 2021

Augmented and virtual reality in spine surgery, current applications and future potentials.

Spine J 2021 Mar 25. Epub 2021 Mar 25.

Spine Service, Department of Orthopaedic Surgery, Massachusetts General Hospital, Boston, MA, USA; Orthopaedic Oncology Service, Department of Orthopaedic Surgery, Massachusetts General Hospital, Boston, MA, USA.

Background Context: The field of Artificial Intelligence (AI) is rapidly advancing, especially with recent improvements in deep learning (DL) techniques. Augmented (AR) and virtual reality (VR) are finding their place in healthcare, and spine surgery is no exception. The unique capabilities and advantages of AR and VR devices include their low cost, flexible integration with other technologies, user-friendly features and their application in navigation systems, which makes them beneficial across different aspects of spine surgery. Despite the use of AR for pedicle screw placement, targeted cervical foraminotomy, bone biopsy, osteotomy planning, and percutaneous intervention, the current applications of AR and VR in spine surgery remain limited.

Purpose: The primary goal of this study was to provide the spine surgeons and clinical researchers with the general information about the current applications, future potentials, and accessibility of AR and VR systems in spine surgery.

Study Design/setting: We reviewed titles of more than 250 journal papers from google scholar and PubMed with search words: augmented reality, virtual reality, spine surgery, and orthopaedic, out of which 89 related papers were selected for abstract review. Finally, full text of 67 papers were analyzed and reviewed.

Methods: The papers were divided into four groups: technological papers, applications in surgery, applications in spine education and training, and general application in orthopaedic. A team of two reviewers performed paper reviews and a thorough web search to ensure the most updated state of the art in each of four group is captured in the review.

Results: In this review we discuss the current state of the art in AR and VR hardware, their preoperative applications and surgical applications in spine surgery. Finally, we discuss the future potentials of AR and VR and their integration with AI, robotic surgery, gaming, and wearables.

Conclusions: AR and VR are promising technologies that will soon become part of standard of care in spine surgery.
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http://dx.doi.org/10.1016/j.spinee.2021.03.018DOI Listing
March 2021

Machine learning prediction models in orthopedic surgery: A systematic review in transparent reporting.

J Orthop Res 2021 Mar 18. Epub 2021 Mar 18.

Orthopedic Oncology Service, Department of Orthopedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Machine learning (ML) studies are becoming increasingly popular in orthopedics but lack a critically appraisal of their adherence to peer-reviewed guidelines. The objective of this review was to (1) evaluate quality and transparent reporting of ML prediction models in orthopedic surgery based on the transparent reporting of multivariable prediction models for individual prognosis or diagnosis (TRIPOD), and (2) assess risk of bias with the Prediction model Risk Of Bias ASsessment Tool. A systematic review was performed to identify all ML prediction studies published in orthopedic surgery through June 18th, 2020. After screening 7138 studies, 59 studies met the study criteria and were included. Two reviewers independently extracted data and discrepancies were resolved by discussion with at least two additional reviewers present. Across all studies, the overall median completeness for the TRIPOD checklist was 53% (interquartile range 47%-60%). The overall risk of bias was low in 44% (n = 26), high in 41% (n = 24), and unclear in 15% (n = 9). High overall risk of bias was driven by incomplete reporting of performance measures, inadequate handling of missing data, and use of small datasets with inadequate outcome numbers. Although the number of ML studies in orthopedic surgery is increasing rapidly, over 40% of the existing models are at high risk of bias. Furthermore, over half incompletely reported their methods and/or performance measures. Until these issues are adequately addressed to give patients and providers trust in ML models, a considerable gap remains between the development of ML prediction models and their implementation in orthopedic practice.
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http://dx.doi.org/10.1002/jor.25036DOI Listing
March 2021

Postoperative adverse events secondary to iatrogenic vascular injury during anterior lumbar spinal surgery.

Spine J 2020 Nov 3. Epub 2020 Nov 3.

Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA.

Background: Anterior lumbar spine surgery (ALSS) requires mobilization of the great vessels, resulting in a high risk of iatrogenic vascular injury (VI). It remains unclear whether VI is associated with increased risk of postoperative complications and other related adverse outcomes.

Purpose: The purpose of this study was to (1) assess the incidence of postoperative complications attributable to VI during ALSS, and (2) outcomes secondary to VI such as procedural blood loss, transfusion of blood products, length of stay (LOS), and in hospital mortality.

Study Design: Retrospective propensity-score matched, case-control study at 2 academic and 3 community medical centers, PATIENT SAMPLE: Patients 18 years of age or older, undergoing ALSS between January 1st, 2000 and July 31st, 2019 were included in this analysis.

Outcome Measures: The primary outcome was the incidence of postoperative complications attributable to VI, such as venous thromboembolism, compartment syndrome, transfusion reaction, limb ischemia, and reoperations. The secondary outcomes included estimated operative blood loss (milliliter), transfused blood products, LOS (days), and in-hospital mortality.

Methods: In total, 1,035 patients were identified, of which 75 (7.2%) had a VI. For comparative analyses, the 75 VI patients were paired with 75 comparable non-VI patients by propensity-score matching. The adequacy of the matching was assessed by testing the standardized mean differences (SMD) between VI and non-VI group (>0.25 SMD).

Results: Two patients (2.7%) had VI-related postoperative complications in the studied period, which consisted of two deep venous thromboembolisms (DVTs) occurring on day 3 and 7 postoperatively. Both DVTs were located in the distal left common iliac vein (CIV). The VI these patients suffered were to the distal inferior vena cava and the left CIV, respectively. Both patients did not develop additional complications in consequence of their DVTs, however, did require systemic anticoagulation and placement of an inferior vena cava filter. There was no statistical difference with the non-VI group where no instances (0%) of postoperative complications were reported (p=.157). No differences were found in LOS or in hospital mortality between the two groups (p=.157 and p=.999, respectively). Intraoperative blood loss and blood transfusion were both found to be higher in the VI group in comparison to the non-VI group (650 mL, interquartile range [IQR] 300-1400 vs. 150 mL, IQR 50-425, p≤.001; 0 units, IQR 0-3 vs. 0 units, IQR 0-1, p=.012, respectively).

Conclusion: This study found a low number of serious postoperative complications related to VI in ALSS. In addition, these complications were not significantly different between the VI and matched non-VI ALSS cohort. Although not significant, the found DVT incidence of 2.7% after VI in ALSS warrants vigilance and preventive measures during the postoperative course of these patients.
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http://dx.doi.org/10.1016/j.spinee.2020.10.031DOI Listing
November 2020

Long-term follow-up and treatment outcomes of conjunctivitis during dupilumab treatment in patients with moderate-to-severe atopic dermatitis.

J Allergy Clin Immunol Pract 2021 Mar 7;9(3):1389-1392.e2. Epub 2020 Oct 7.

Department of Dermatology and Allergology, National Expertise Center for Atopic Dermatitis, University Medical Center Utrecht, Utrecht, the Netherlands.

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http://dx.doi.org/10.1016/j.jaip.2020.09.042DOI Listing
March 2021

Off-Hour Surgery Among Orthopedic Subspecialties at an Urban, Quaternary-Care, Level 1 Trauma Center.

J Hand Surg Am 2016 Dec 28;41(12):1153-1158. Epub 2016 Oct 28.

Hand Service, Department of Orthopedic Surgery, Massachusetts General Hospital, Boston, MA. Electronic address:

Purpose: We sought to determine and quantify which subspecialties of orthopedic surgeons are operating off hours in an urban, quaternary-care, level 1 trauma center.

Materials And Methods: We used our clinical registry to identify 43,211 orthopedic surgeries performed between January 2008 and December 2011. Our outcome measures were the number and proportion of off-hour surgeries performed as well as the number and proportion of off-hours per subspecialty. The denominators were the total number of surgeries and the total number of surgical hours worked per subspecialty. Subspecialties-based on the primary surgeon who performed the surgery-were arthroplasty, foot and ankle, hand, pediatrics, shoulder, spine, sports, orthopedic trauma, and orthopedic oncology.

Results: A total of 2,431 (5.6%) surgeries were off-hours; the overall ratio of off-hour to on-hour surgeries was 1 to 17. There was a difference in the proportion of off-hour surgeries performed among orthopedic subspecialties: trauma (ratio, 1:5) and pediatric specialists (ratio, 1:5) had the lowest ratio, and shoulder (ratio, 1:152) and sports (ratio, 1:98) specialists the highest. The total number of surgical hours among all specialties was 59,026; of these hours, 3,833 (6.5%) were off-hour. The ratio of off-hour to on-hour surgical hours was 1 to 14. There was a difference in proportion of hours worked off-hour among orthopedic subspecialties; the ratios were greatest for trauma (1:5) and hand (1:5) specialists and the least for shoulder (1:157) and sports (1:92) specialists. Seven percent of hand surgery cases were off-hour, and 16% of the total surgical hours worked by hand surgeons were off-hour.

Conclusions: In an urban, academic, level 1 trauma and microvascular replantation regional referral hospital, there is a large difference in off-hour surgical volume and duration among orthopedic subspecialties: trauma, pediatric, and hand surgeons performed more off-hour work than their colleagues, with hand and pediatric surgeons the most likely to be working at night.

Clinical Relevance: These data can inform how we organize, value, and incentivize off-hour care.
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http://dx.doi.org/10.1016/j.jhsa.2016.09.017DOI Listing
December 2016